The most accurate current denoisers are trained on a representative dataset consisting of noisy images and their clean counterparts. The earliest method to do this with a neural network was [1]}. This was heavily refined in both the works of Mao et al. [2]} and Zhang et al. [3]} to achieve results that are still among the best achievable today. A more recent approach is [4]} which uses a two-module approach to push accuracy even further.
